Transmitter Content and Afferent Connections of Estrogen-Sensitive Progestin Receptor-Containing Neurons in the Primate Hypothalamus
Bibliographic record
Abstract
Progestin receptor-containing cells in the hypothalamus of the adult female green monkey (Cercopithecus aethiops) were examined by double-label immunocytochemical methods to determine their anatomical location, neurotransmitter content and afferent connections. Animals were ovariectomized and administered either estradiol valerate or the oil injection vehicle, and were sacrificed after 10 days of treatment. Using a monoclonal antibody raised against rabbit uterine progestin receptor (PR), the distribution of PR-immunoreactive cells in the mediobasal hypothalamus and the effect of estrogen treatment on this distribution was determined. PR-immunoreactive cells were found throughout the ventromedial nucleus (VMN), in the area between the VMN and fornix, and in the medial portion of the infundibular nucleus. Estrogen treatment dramatically increased both the number of labeled cells and the intensity of immunoreaction product in these regions. In double-immunostained sections, boutons immunoreactive for antigens indicative of serotonin, pro-opiomelanocortin derived peptides, GABA, catecholamine, neuropeptide Y, substance P, cholecystokinin, and somatostatin were demonstrated to establish synaptic contact with the soma of PR-immunoreactive hypothalamic neurons. In colchicine-pretreated animals, all PR-containing neurons in the mediobasal hypothalamus were found to contain immunoreactivity for glutamic acid decarboxylase, the enzyme required for synthesis of GABA. No evidence of colocalization with other antigens, including LHRH, was observed. Because LHRH neurons are known to receive a rich GABAergic innervation PR-containing GABAergic cells may represent steroid-sensitive sites of integration for inputs from other neural systems involved in the control of gonadotropin secretion.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".